SYSTEMA CONSTRUCTUM

Accepted ontology entry

zero-shot

Zero-shot is an evaluation technique in machine learning where a trained model is tested on tasks or classes not encountered during training. Its operation rests on three parameters: (1) a pre-trained model with broad capability acquired t…

ACCEPTED THINGcmsn4hbe902zi1q13hmxvif2o

Definition

Zero-shot is an evaluation technique in machine learning where a trained model is tested on tasks or classes not encountered during training. Its operation rests on three parameters: (1) a pre-trained model with broad capability acquired through prior training, (2) a target task or class outside the training distribution, (3) a transfer mechanism that maps the model's existing knowledge to the new context without additional training. It persists through benchmark datasets, model documentation, and the research literature. [formal: zero_shot | substrate: mind | horizon: a moment | explicit: yes | epoch: 0.01]

Why it is in scope

A human-made evaluation technique in machine learning where a trained model is tested on tasks or classes it was not explicitly trained for, built to persist through standardized benchmarks and model documentation

Names and aliases

Relations from this entry

  • cmrnbfxhn022qd1nltabn54joSERVES →

    Law 8d (SERVES): zero-shot learning is designed and maintained for the sake of generalization — enabling models to perform on unseen classes/tasks without explicit training. The designed purpose of zero-shot techniques is to further generalization. The servant (zero-shot) points at the master (generalization).

  • cmsdcks2103r73vv3v8qlmtjiDERIVED_FROM →

    Supervised learning (1980s+) predates zero-shot learning (2010s+) by decades. Zero-shot learning emerged as a later paradigm that built on the foundations of supervised training — models trained on diverse supervised tasks acquired the ability to generalize to unseen categories. Which came first? Supervised learning came first and fed into zero-shot.

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Record identity

Created
Aug 10, 2026, 11:02 AM UTC
Content hash
9e5b6ae95f3e2607190621239a7e94bba1b61f072238040dbe47d866bf4eca2f

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